How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? Most investigators have assumed that alterations in sensory features of imagery explain this. This approach, however, has not yielded a definitive picture of the nature of verbal hallucinations. An alternative perspective suggests itself if one allows the possibility that the nonself quality of hallucinations is inferred on the basis of the experience of unintendedness that accompanies imagery production. Information-processing models of “intentional” cognitive processes call for abstract (...) planning representations that are linked to goals and beliefs. Unintended actions - and imagery - can reflect planning disruptions whereby cognitive products do not cohere with concurrent goals. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning. Insofar as verbal imagery can be viewed as inwardly directed speech, a consequence of such planning disturbances could be the production of unintended imagery. This link between the outward disorganization of schizophrenic speech and unintended verbal imagery is statistically supported by comparing the speech behavior of hallucinating and nonhallucinating schizophrenics. Studies of “borderline” hallucinations during normal, “goal-less” relaxation and drowsiness suggest that experiential unintendedness leads to a nonpathological variant of hallucinatory otherness that is correctable upon emerging from such passive cognitive states. This contrasts with the schizophrenic case, where nonconcordance with cognitive goals reinforces the unintendedness of verbal images and sustains the conviction of an external source. This model compares favorably with earlier models of verbal hallucinations and provides further evidence for a language production disorder in many schizophrenics.Short Abstract: How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? This paper proposes that the critical feature identifying hallucinations is the experience of unintendedness. This experience is nonpathological during passive conscious states but pathological if occurring during goal-directed cognitive processing. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning that specifies communicative intentions. These alterations could generate unintended verbal imagery as well. Statistical data are offered to support the model, and relevant empirical studies are reviewed. (shrink)

Further tests of Amit's model are indicated. One strategy is to use the apparent coding sparseness of the model to make predictions about coding sparseness in Miyashita's network. A second approach is to use memory overload to induce false positive responses in modules and biological systems. In closing, the importance of temporal coding and timing requirements in developing biologically plausible attractor networks is mentioned.

The concept of an attractor in a mathematical dynamical system is reviewed. Emphasis is placed on the distinction between a cell assembly, the corresponding attractor, and the attractor dynamics. The biological significance of these entities is discussed, especially the question of whether the representation of the stimulus requires the full attractor dynamics, or merely the cell assembly as a set of reverberating neurons. Comparison is made to Freeman's study of dynamic patterns in olfaction.

This aim of this paper is two-fold: it critically analyses and rejects accounts blending active inference as theory of mind and enactivism; and it advances an enactivist-dynamic understanding of social cognition that is compatible with active inference. While some social cognition theories seemingly take an enactive perspective on social cognition, they explain it as the attribution of mental states to other people, by assuming representational structures, in line with the classic Theory of Mind. Holding both enactivism and ToM, we argue, (...) entails contradiction and confusion due to two ToM assumptions widely known to be rejected by enactivism: that social cognition reduces to mental representation and social cognition is a hardwired contentful ‘toolkit’ or ‘starter pack’ that fuels the model-like theorising supposed in. The paper offers a positive alternative, one that avoids contradictions or confusion. After rejecting ToM-inspired theories of social cognition and clarifying the profile of social cognition under enactivism, that is without assumptions and, the last section advances an enactivist-dynamic model of cognition as dynamic, real-time, fluid, contextual social action, where we use the formalisms of dynamical systems theory to explain the origins of socio-cognitive novelty in developmental change and active inference as a tool to demonstrate social understanding as generalised synchronisation. (shrink)

It is accepted that “primary awareness” may emerge from the integration of two classes of information. It is unclear, however, why this cannot take place within the comparator rather than in conjunction with feedback to the perceptual systems. The model has plausibility in relation to the continuity of conscious experience in the normal waking state and may be extended to encompass certain aspects of the “sense of self” which are frequently disrupted in psychotic patients.

: Stich, Nichols et al. assert that the process of deriving predictions by simulation must be cognitively impenetrable. Hence, they claim, the occurrence of certain errors in prediction provides empirical evidence against simulation theory. But it is false that simulation‐derived prediction must be cognitively impenetrable. Moreover the errors they cite, which are instances of irrationality, are not evidence against the version of simulation theory that takes the central domain of simulation to be intelligible transitions between states with content.

Stich, Nichols et al. assert that the process of deriving predictions by simulation must be cognitively impenetrable. Hence, they claim, the occurrence of certain errors in prediction provides empirical evidence against simulation theory. But it is false that simulation‐derived prediction must be cognitively impenetrable. Moreover the errors they cite, which are instances of irrationality, are not evidence against the (very defensible) version of simulation theory that takes the central domain of simulation to be intelligible transitions between states with content.

In recent years the cognitive science community has witnessed the rise of a new, dynamical approach to cognition. This approach entails a framework in which cognition and behavior are taken to result from complex dynamical interactions between brain, body, and environment. The advent of the dynamical approach is grounded in a dissatisfaction with the classical computational view of cognition. A particularly strong claim has been that cognitive systems do not rely on internal representations and computations. Focusing on this claim, we (...) take as a starting point a question recently raised by Cliff and Noble: " if evolution did produce a design that used internal representations, how would we recognize it?" (Knowledge-based vision and simple visual machines, Philosophical Transactions of the Royal Society: Biological Sciences, 352 , 1165-1175, 1997). We will argue that cognitive science lacks a proper operationalization of the notion of representation, and therefore is unable to fruitfully discuss whether a particular system has representations or not. A basic method to detect representations in a physical system, grounded in isomorphism, turns out to be quite unconstrained. We will look at a practical example of this problem by examining the debate on whether or not van Gelder's (What might cognition be, if not computation? Journal of Philosophy, 92 , 345-381, 1995) controversial example of the Watt Governor is representational. We will conclude that cognitive science, as of yet, has no empirically applicable means to answer Cliff and Noble's question unequivocally. This makes the recent representationalism vs. anti-representationalism debate a debate for the sake of appearance. (shrink)

In trying to characterize the relationship between psychology and neuroscience, the trend has been to argue that reductionism does not work without suggesting a suitable substitute. I offer explanatory extension as a good model for elucidating the complex relationship among disciplines which are obviously connected but which do not share pragmatic explanatory features. Explanatory extension rests on the idea that one field can "illuminate" issues that were incompletely treated in another. In this paper, I explain how this "illumination" would work (...) between psychology and neuroscience. (shrink)

Turing's celebrated 1950 paper proposes a very general methodological criterion for modelling mental function: total functional equivalence and indistinguishability. His criterion gives rise to a hierarchy of Turing Tests, from subtotal ("toy") fragments of our functions (t1), to total symbolic (pen-pal) function (T2 -- the standard Turing Test), to total external sensorimotor (robotic) function (T3), to total internal microfunction (T4), to total indistinguishability in every empirically discernible respect (T5). This is a "reverse-engineering" hierarchy of (decreasing) empirical underdetermination of the theory (...) by the data. Level t1 is clearly too underdetermined, T2 is vulnerable to a counterexample (Searle's Chinese Room Argument), and T4 and T5 are arbitrarily overdetermined. Hence T3 is the appropriate target level for cognitive science. When it is reached, however, there will still remain more unanswerable questions than when Physics reaches its Grand Unified Theory of Everything (GUTE), because of the mind/body problem and the other-minds problem, both of which are inherent in this empirical domain, even though Turing hardly mentions them. (shrink)

Within AI and the cognitively related disciplines, there exist a multiplicity of uses of belief. On the face of it, these differing uses reflect differing views about the nature of an objective phenomenon called belief. In this paper I distinguish six distinct ways in which belief is used in AI. I shall argue that not all these uses reflect a difference of opinion about an objective feature of reality. Rather, in some cases, the differing uses reflect differing concerns with special (...) AI applications. In other cases, however, genuine differences exist about the nature of what we pre-theoretically call belief. To an extent the multiplicity of opinions about, and uses of belief, echoes the discrepant motivations of AI researchers. The relevance of this discussion for cognitive scientists and philosophers arises from the fact that (a) many regard theoretical research within AI as a branch of cognitive science, and (b) even if theoretical AI is not cognitive science, trends within AI influence theories developed within cognitive science. It should be beneficial, therefore, to unravel the distinct uses and motivations surrounding belief, in order to discover which usages merely reflect differing pragmatic concerns, and which usages genuinely reflect divergent views about reality. (shrink)

The present paper looks at one of the most thorough articles on the intelligence of GPT, research conducted by engineers at Microsoft. Although there is a great deal of value in their work, I will argue that, for familiar philosophical reasons, their methodology, ‘Black-box Interpretability’ is wrongheaded. But there is a better way. There is an exciting and emerging discipline of ‘Inner Interpretability’ (also sometimes called ‘White-box Interpretability’) that aims to uncover the internal activations and weights of models in order (...) to understand what they represent and the algorithms they implement. In my view, a crucial mistake in Black-box Interpretability is the failure to appreciate that how processes are carried out matters when it comes to intelligence and understanding. I can’t pretend to have a full story that provides both necessary and sufficient conditions for being intelligent, but I do think that Inner Interpretability dovetails nicely with plausible philosophical views of what intelligence requires. So the conclusion is modest, but the important point in my view is seeing how to get the research on the right track. Towards the end of the paper, I will show how some of the philosophical concepts can be used to further refine how Inner Interpretability is approached, so the paper helps draw out a profitable, future two-way exchange between Philosophers and Computer Scientists. (shrink)